Personal identification has become one of the most important terms in our society regarding access control, crime and forensic identification, banking and also computer system. The fingerprint is the most used biometric feature caused by its unique, universality and stability. The fingerprint is widely used as a security feature for forensic recognition, building access, automatic teller machine (ATM) authentication or payment. Fingerprint recognition could be grouped in two various forms, verification and identification. Verification compares one on one fingerprint data. Identification is matching input fingerprint with data that saved in the database. In this paper, we measure the performance of the memetic algorithm to process the image fingerprints dataset. Before we run this algorithm, we divide our fingerprints into four groups according to its characteristics and make 15 specimens of data, do four partial tests and at the last of work we measure all computation time.

Hybrid models of the precipitation spillover process that are embedded with high unpredictability, nonstationarity, and non-linearity inboth spatial and worldly scales can give significant results in rainfall forecasting. Considering this, various neural network models have been applied to reproduce this complex process. Neural Network is an information processing system that has characteristics similar to biological terms. A neural network is a machine designed to model the workings of the human brain in performing certain functions or tasks. In general, FFNNs are trained to use the Backpropagation algorithm to get their weights. Backpropagation can work well on simple training problems, but its performance will decrease and be trapped in a local minimum when applied to data that has enormous complexity. Therefore, metaheuristic operations are needed using Genetic Algorithms (AG). In this paper, a detailed discussion of the FFNN-AG step construction will be given, which is a search algorithm based on selection and genetic mechanisms to determine global optimum and evaluation of previous paper related to this.